The difference between numerical weather prediction models grows with time. In most cases these days, the model of choice is the one run in London by the ECMWF.

Besides the increasing gap in weather satellite technology, Europe and Japan are also well ahead in computer power available for numerical weather prediction models. Almost every U.S. forecast meteorologist this winter has relied on the global model from the European Center for Medium Range Weather Forecasting, (based in London) rather than the NOAA Global Forecast system. Short range forecasts are handled well by the NOAA high-resolution models centered over North America, but for forecasts beyond three days a global model is needed.

Cliff Mass has an excellent post on his blog about the serious gap in computer power and I reprint it here with his permission. While I do not agree with everything here, (For instance, the computer needs are very high for climate models, and they are vital to predict the effects of increasing greenhouse gases.) but make no mistake about it, the 7 day forecast you see on TV everyday is based more and more on a model based in Europe, not in America.

The U.S. Weather Prediction Computer Gap

It happened again. A major storm hit the northeast U.S. and the U.S. global model lagged badly behind the predictions of the European Center for Medium Range Weather Forecasting (ECMWF) . Just as with Sandy. To illustrate, take a look at the 120-hr forecast of sea level pressure from the ECMWF and U.S. GFS models valid at 4 PM PST Friday, Feb. 9. First, the observed situation (colors, the winds at 850 hPa; solid lines, isobars, lines of constant pressure):

A deep low center right off the coast. A major snow and wind threat.

And there is the 120 hr ECMWF forecast, clearly showing a major storm.

The U.S. GFS model for the same time? Only predicted a minor trough with little weather (see graphic below). Not good. The U.S. model was just as bad at 108 hr out. Disappointing.

The National Weather Service’s own statistics show that the American model had a substantial drop in skill globally during the critical period in question, with inferior performance (black line) compared to the European Center, the UKMET office, the Canadian Meteorological Center, and even the U.S. Navy (see figure, closer to one is better).

As I have described in my previous blogs (including here and here), much of the inferiority of U.S. global numerical weather prediction can be traced to the third-rate operational computer resources available to the National Weather Service (NWS)’s Environmental Modeling Center (EMC), an inferiority that can only be characterized as a national embarrassment. And as I shall document here, the NWS weather prediction computers are not only inferior to those of other national weather services, but also to NOAA’s computers for weather research and to U.S. climate prediction machines. Be prepared to be shocked, angry, and disappointed. And to take action to change this situation.

Let’s begin by comparing the most powerful weather prediction computers used by various countries around the world (see graphic below). Japan and ECMWF are the leaders with about .8 petaflop machines, followed by England (UKMET), S. Korea, and Canada. The U.S. is at the bottom of the barrel, with about TEN PERCENT of the capacity of the leaders.

Yes, we are talking about the richest nation in the world, and one of the most vulnerable to severe weather.

What makes this even worse is that the U.S. has such a large area (including Alaska, Hawaii, the U.S. mainland, Puerto Rico and the Virgin Islands).

Got your juices going yet? You haven’t seen anything!

Let’s compare the computer power availability for operational numerical weather prediction in the NWS to that available to its parent agency, NOAA, for weather research (see graphic). The NWS operational machine is dwarfed by the NOAA computers that are available for research. The new NOAA Fairmont machine is five times more powerful, and the NOAA Earth Systems Research Lab/Global Systems Division has TWO far bigger machines. So operational prediction, which saves lives and promotes the economy of the nation, gets crippled by lack of computer power, while researchers get the big machines. Folks, some administrators in NOAA are making very bad decisions. And their bosses in the Department of Commerce are going along with it.

Not steamed yet? Then take a look at a comparison between the U.S. operational weather prediction computer capacity and a few of the U.S. machines available for climate research (overwhelming used for long-term climate simulations). I did not list every major computer available for climate. Climate-dedicated computers absolutely dwarf operational weather prediction computer capacity, so much so that you can barely see the operational computer resource on this plot! Just considering the machines shown in the figure, climate simulation has about FIVE HUNDRED TIMES the computer power available for operational weather prediction.

Folks, this is outrageous. Weather prediction is critical for the U.S. economy and for public safety. And even if you are worried about climate change, the number one thing one needs to encourage resilience in a changing climate is to have good weather prediction! What is the logic for giving climate research hundreds of times more computer power than weather prediction? It makes no sense from a rational viewpoint.

A big part of the problem is that NOAA management has decided to put priority on the oceans and climate while they short-change weather prediction. This has been a deliberate and long-term policy. Unfortunately, the U.S. Congress has not reined them in. The irony is that NOAA understands how important and popular the National Weather Service is and demands that NWS products have NOAA stamped all over it–while draining critical resources the NWS requires to do a proper job.

The time to fix this self-inflicted problem is now. There is a great deal of money in the Hurricane Sandy relief bill for improving hurricane and storm prediction or storm-related infrastructure (over 100 million dollars). Some of this money should be used to fix the NWS computer deficiency (it would take about 50 million dollars). There is nothing that would more effectively improve hurricane prediction than dealing with the computer gap. We are not talking about increasing NWS computer capacity by 30%: it needs to be increased by 10-100 times to properly serve the nation. Consider that NOAA is planning on spending 44 millionto replace the wings on two hurricane hunter aircraft: the same money would revolutionize and greatly improve U.S. weather prediction if used on computers. If the Sandy money is not available, other funds should be found. Enhanced computers is absolutely core infrastructure for the U.S. and would pay for itself many, many times over. So many other nations understand this and have committed the necessary financial resources to secure bigger computers for their weather services.

NOAA folks have proven themselves to be unable to deal with this issue, so I recommend you contact your Congressman or Senator to complain. Only Congress has the clout to fix the situation. And only by your complaining and making this a major issue, will Congress take it seriously.

Comments

9 Comments

Power does not necessarily equal accuracy. More ensembles does not necessarily equal better accuracy if your model is not perfect. The US and UK forecast models are still consistently the best in the world overall. More computing power is always desirable, especially if one seeks to improve things, but it is not necessarily the limiting factor in forecast ability.

Very true Georgina and of course there are other limiting factors. That sauid the skill of the euro has been significantly better than the GFS which is truncated because of computer resources at around 180 hours. Thuis would not be needed if we had more resources.

What if… it seems like the more common layman’s argument against climate science is the “you can’t forecast next week, so you can’t predict next decade”. Does a limit on NWS computing capability, as described here, allow that argument to remain status quo? What if, those budgeting decisions were intentional, with this thought in mind?

As a layman, this sounds like pitch to management to get more compute power. Tools and power do not deliver results as Georgine observed earlier. It is a combination of tools, power, intellect, capability, expertise, etc. that delivers results. It would have been nice to see prediction accuracy over time i.e how often are non-US forecasts accurate vs US forecasts. This should also take into account weather variability i.e. getting predictions right in a part of the world where the weather is more stable/even and comparing it with a forecast where weather tends to changes on a hourly basis is not a good apples to apples comparison.

I agree that numerical weather prediction is not the sole factor in making a decent forecast but they are indeed a MAJOR factor, and accurate forecasts would be impossible without them. I do not work for NOAA however, so this post was not about getting mgt. to spend more money. I can tell you that european forecasts are quite good as are Japan, NZ and Australian forecasts. Comparisons between the skill of the U.S. global model and the euro model have been done and they show the euro model to be significantly better which is no surprise since it is a more complex model. The U.S. does not have the computer power to do the same.

Oh, and this is a good time to remind everyone that comments must be signed. I have overlooked this in a few cases this week but no longer.

umm, maybe I’m missing something here… what does it matter?
Does the world need 10… or 5… or even 3 organizations who can forecast the weather on this level? If the Europeans are doing such a great job why not just get the data from them? Who says (or cares) that the weather report has a ‘Made in the USA’ stamp on it?

As the article points out, forecasting relies on a global perspective. It doesn’t need multiple myopic viewpoints saying the same thing.

I’m serious here. In fact I’d argue the complete opposite to this article…. turn off those GFS servers (which will reduce the carbon footprint in the process, aiding the long-term climate change models (yes, I’m being sarcastic here)), or reallocate them for something that no one else is doing.

Well we certainly could shut down the GFS model but the Europeans would then not be getting our model data and the cost to use their data would likely be very high. What you are missing though is that long range forecast techniques use ensemble forecasting which requires multiple runs of an NWP model with slightly differing initial conditions and you also have longer range climate forecast system models based off the GFS which would also go away. Models are also tuned to the area of prime interest, and if we are using the ECMWF, it would not likely be the U.S. It gets to be a prime national security issue as well.

If we want to improve forecasting in the future as much as we have in the past decades then we also have no choice in running NWP models and experimenting with them to improve their forecasts. The other countries with more computer power for NWP made the choice to do just that and have progressed rapidly. If for some reason in the future the ECMWF folks decided that they wanted to double the cost of the data, we would have no choice but to pay.

So in short the idea is basically a rather silly knee jerk reaction no? Then again we seem to be turning man space flight over to the Russians, and most of the new green technology is being developed outside the U.S.as well. Perhaps we should admit our time as a world leader is over and quietly sink back to 2nd world status. If you have traveled widely in Europe lately (I have), you might be forgiven for thinking we already have.

I hear you, Dan, but why do Americans (I’m not one, btw) think they have to be the world leader in every respect?
What’s wrong with letting those that excel at a task becoming the authority on that subject? Why can’t the US acknowledge that the Europeans do a better job at near-range forecasting and embrace that, rather than setting out to beat them (or rueing the fact they’re behind, or pouring millions of dollars into being an also-ran).

Science is a global endeavor. There’s no reason that one country should hold dominion over it, or over any single aspect of it. In the case of weather forecasting, why not have a global, multi-national organization that’s responsible, that makes its data available at reasonable rates, and accepts input from anywhere. The ‘Us vs. Them’ culture seems pointless.

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About Dan

Dan Satterfield has worked as an on air meteorologist for 32 years in Oklahoma, Florida and Alabama. Forecasting weather is Dan's job, but all of Earth Science is his passion. This journal is where Dan writes about things he has too little time for on air. Dan blogs about peer-reviewed Earth science for Junior High level audiences and up.MORE ABOUT DAN >>

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